RSA models

library(colorout)
library(here)
library(data.table)
library(knitr)
library(dplyr)
library(tidyr)
library(ggplot2)
source(here("src", "stroop-rsa-pc.R"))

opts_chunk$set(results = FALSE)
options(dplyr.summarise.inform = FALSE)
theme_set(theme_bw(base_size = 8))


plot_models <- function(session, ttype_subset, measure_type) {
    if (measure_type == "similarity") {
        meas_type <- "crcor"
    } else if (measure_type == "cvdistance") {
        meas_type <- "cveuc"
    }
    for (mod in models[[meas_type]]) {
        rdm_models <- 
            read_model_rdm(model = mod, measure_type = measure_type, session = session, ttype_subset = ttype_subset)
        p <- 
            rdm_models %>% 
            melt_mat %>% 
            plot_melted_mat(add_greyscale_gradient = FALSE, rotate_xaxis_text = TRUE) + 
            geom_text(aes(label = round(value, 1)), color = "white") +
            scale_fill_viridis_c() +
            labs(title = mod)

        print(p)
    }
}

baseline session

bias items

cross-run correlation

plot_models("baseline", "bias", "similarity")

cross-validated distance

plot_models("baseline", "bias", "cvdistance")

pc50 items

cross-run correlation

plot_models("baseline", "pc50", "similarity")

cross-validated distance

plot_models("baseline", "pc50", "cvdistance")

proactive session

bias items

cross-run correlation

plot_models("proactive", "bias", "similarity")

cross-validated distance

plot_models("proactive", "bias", "cvdistance")

pc50 items

cross-run correlation

plot_models("proactive", "pc50", "similarity")

cross-validated distance

plot_models("proactive", "pc50", "cvdistance")

reactive session

bias items

cross-run correlation

plot_models("reactive", "bias", "similarity")

cross-validated distance

plot_models("reactive", "bias", "cvdistance")

pc50 items

cross-run correlation

plot_models("reactive", "pc50", "similarity")

cross-validated distance

plot_models("reactive", "pc50", "cvdistance")